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--- abstract: |- This paper presents a novel self-organising neural network. It has been developed for use as a simplified model of cortical development. Unlike many other models of topological map formation all synaptic weights start at zero strength (so that synaptogenesis might be modelled). In addition, the algorithm works with the same format of encoding for both inputs to and outputs from the network (so that the transfer and recoding of information between cortical regions might be modelled). altloc: [] chapter: ~ commentary: ~ commref: ~ confdates: 1998 conference: ' 6th European Symposium on Artificial Neural Networks (ESANN98)' confloc: Brugges contact_email: ~ creators_id: [] creators_name: - family: Spratling given: Michael honourific: '' lineage: '' - family: Hayes given: Gillian honourific: '' lineage: '' date: 1998 date_type: published datestamp: 2000-11-15 department: ~ dir: disk0/00/00/11/07 edit_lock_since: ~ edit_lock_until: ~ edit_lock_user: ~ editors_id: [] editors_name: [] eprint_status: archive eprintid: 1107 fileinfo: /style/images/fileicons/application_postscript.png;/1107/2/map_alg.ps full_text_status: public importid: ~ institution: ~ isbn: ~ ispublished: pub issn: ~ item_issues_comment: [] item_issues_count: 0 item_issues_description: [] item_issues_id: [] item_issues_reported_by: [] item_issues_resolved_by: [] item_issues_status: [] item_issues_timestamp: [] item_issues_type: [] keywords: 'neural networks, self-organisation' lastmod: 2011-03-11 08:54:26 latitude: ~ longitude: ~ metadata_visibility: show note: ~ number: ~ pagerange: 333-338 pubdom: FALSE publication: ~ publisher: ~ refereed: TRUE referencetext: ~ relation_type: [] relation_uri: [] reportno: ~ rev_number: 10 series: ~ source: ~ status_changed: 2007-09-12 16:36:26 subjects: - comp-sci-neural-nets succeeds: ~ suggestions: ~ sword_depositor: ~ sword_slug: ~ thesistype: ~ title: A self-organising neural network for modelling cortical development type: confpaper userid: 1040 volume: ~